-
Notifications
You must be signed in to change notification settings - Fork 68
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
Shannon Axelrod
committed
Sep 27, 2019
1 parent
89a13f2
commit f2148b4
Showing
15 changed files
with
501 additions
and
76 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Empty file.
167 changes: 167 additions & 0 deletions
167
starfish/core/spots/DecodeSpots/test/test_nearest_neighbor_trace_builder.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,167 @@ | ||
| import numpy as np | ||
| from scipy.ndimage.filters import gaussian_filter | ||
|
|
||
| from starfish import ImageStack | ||
| from starfish.core.spots.DecodeSpots.trace_builders import build_traces_nearest_neighbors | ||
| from starfish.core.spots.FindSpots import BlobDetector | ||
| from starfish.core.types import Axes | ||
|
|
||
|
|
||
| def traversing_code() -> ImageStack: | ||
| """this code walks in a sequential direction, and should only be detectable from some anchors""" | ||
| img = np.zeros((3, 2, 20, 50, 50), dtype=np.float32) | ||
|
|
||
| # code 1 | ||
| img[0, 0, 5, 35, 35] = 10 | ||
| img[1, 1, 5, 32, 32] = 10 | ||
| img[2, 0, 5, 29, 29] = 10 | ||
|
|
||
| # blur points | ||
| gaussian_filter(img, (0, 0, 0.5, 1.5, 1.5), output=img) | ||
|
|
||
| return ImageStack.from_numpy(img) | ||
|
|
||
|
|
||
| def multiple_possible_neighbors() -> ImageStack: | ||
| """this image is intended to be tested with anchor_round in {0, 1}, last round has more spots""" | ||
| img = np.zeros((3, 2, 20, 50, 50), dtype=np.float32) | ||
|
|
||
| # round 1 | ||
| img[0, 0, 5, 20, 40] = 10 | ||
| img[0, 0, 5, 40, 20] = 10 | ||
|
|
||
| # round 2 | ||
| img[1, 1, 5, 20, 40] = 10 | ||
| img[1, 1, 5, 40, 20] = 10 | ||
|
|
||
| # round 3 | ||
| img[2, 0, 5, 20, 40] = 10 | ||
| img[2, 0, 5, 35, 35] = 10 | ||
| img[2, 0, 5, 40, 20] = 10 | ||
|
|
||
| # blur points | ||
| gaussian_filter(img, (0, 0, 0.5, 1.5, 1.5), output=img) | ||
|
|
||
| return ImageStack.from_numpy(img) | ||
|
|
||
|
|
||
| def jitter_code() -> ImageStack: | ||
| """this code has some minor jitter <= 3px at the most distant point""" | ||
| img = np.zeros((3, 2, 20, 50, 50), dtype=np.float32) | ||
|
|
||
| # code 1 | ||
| img[0, 0, 5, 35, 35] = 10 | ||
| img[1, 1, 5, 34, 35] = 10 | ||
| img[2, 0, 6, 35, 33] = 10 | ||
|
|
||
| # blur points | ||
| gaussian_filter(img, (0, 0, 0.5, 1.5, 1.5), output=img) | ||
|
|
||
| return ImageStack.from_numpy(img) | ||
|
|
||
|
|
||
| def two_perfect_codes() -> ImageStack: | ||
| """this code has no jitter""" | ||
| img = np.zeros((3, 2, 20, 50, 50), dtype=np.float32) | ||
|
|
||
| # code 1 | ||
| img[0, 0, 5, 20, 35] = 10 | ||
| img[1, 1, 5, 20, 35] = 10 | ||
| img[2, 0, 5, 20, 35] = 10 | ||
|
|
||
| # code 1 | ||
| img[0, 0, 5, 40, 45] = 10 | ||
| img[1, 1, 5, 40, 45] = 10 | ||
| img[2, 0, 5, 40, 45] = 10 | ||
|
|
||
| # blur points | ||
| gaussian_filter(img, (0, 0, 0.5, 1.5, 1.5), output=img) | ||
|
|
||
| return ImageStack.from_numpy(img) | ||
|
|
||
|
|
||
| def blob_detector(): | ||
| return BlobDetector(min_sigma=1, max_sigma=4, num_sigma=30, threshold=.1) | ||
|
|
||
|
|
||
| def test_local_search_blob_detector_two_codes(): | ||
| stack = two_perfect_codes() | ||
| bd = blob_detector() | ||
| spot_results = bd.run(stack, n_processes=1) | ||
|
|
||
| intensity_table = build_traces_nearest_neighbors(spot_results=spot_results, anchor_round=1, | ||
| search_radius=1) | ||
|
|
||
| assert intensity_table.shape == (2, 2, 3) | ||
| assert np.all(intensity_table[0][Axes.X.value] == 45) | ||
| assert np.all(intensity_table[0][Axes.Y.value] == 40) | ||
| assert np.all(intensity_table[0][Axes.ZPLANE.value] == 5) | ||
|
|
||
|
|
||
| def test_local_search_blob_detector_jitter_code(): | ||
| stack = jitter_code() | ||
|
|
||
| bd = blob_detector() | ||
| spot_results = bd.run(stack, n_processes=1) | ||
| intensity_table = build_traces_nearest_neighbors(spot_results=spot_results, anchor_round=1, | ||
| search_radius=3) | ||
|
|
||
| assert intensity_table.shape == (1, 2, 3) | ||
| f, c, r = np.where(~intensity_table.isnull()) | ||
| assert np.all(f == np.array([0, 0, 0])) | ||
| assert np.all(c == np.array([0, 0, 1])) | ||
| assert np.all(r == np.array([0, 2, 1])) | ||
|
|
||
| # test again with smaller search radius | ||
| bd = BlobDetector(min_sigma=1, max_sigma=4, num_sigma=30, threshold=.1) | ||
| per_tile_spot_results = bd.run(stack, n_processes=1) | ||
|
|
||
| intensity_table = build_traces_nearest_neighbors(spot_results=per_tile_spot_results, | ||
| anchor_round=0, | ||
| search_radius=1) | ||
|
|
||
| assert intensity_table.shape == (1, 2, 3) | ||
| f, c, r = np.where(~intensity_table.isnull()) | ||
| assert np.all(f == np.array([0])) | ||
| assert np.all(c == np.array([0])) | ||
| assert np.all(r == np.array([0])) | ||
|
|
||
|
|
||
| def test_local_search_blob_detector_traversing_code(): | ||
| stack = traversing_code() | ||
|
|
||
| bd = blob_detector() | ||
| spot_results = bd.run(stack, n_processes=1) | ||
| intensity_table = build_traces_nearest_neighbors(spot_results=spot_results, anchor_round=0, | ||
| search_radius=5) | ||
|
|
||
| assert intensity_table.shape == (1, 2, 3) | ||
| f, c, r = np.where(~intensity_table.isnull()) | ||
| assert np.all(f == np.array([0, 0])) | ||
| assert np.all(c == np.array([0, 1])) | ||
| assert np.all(r == np.array([0, 1])) | ||
|
|
||
| bd = blob_detector() | ||
| spot_results = bd.run(stack, n_processes=1) | ||
| intensity_table = build_traces_nearest_neighbors(spot_results=spot_results, anchor_round=1, | ||
| search_radius=5) | ||
|
|
||
| f, c, r = np.where(~intensity_table.isnull()) | ||
| assert np.all(f == np.array([0, 0, 0])) | ||
| assert np.all(c == np.array([0, 0, 1])) | ||
| assert np.all(r == np.array([0, 2, 1])) | ||
|
|
||
|
|
||
| def test_local_search_blob_detector_multiple_neighbors(): | ||
| stack = multiple_possible_neighbors() | ||
|
|
||
| bd = blob_detector() | ||
| spot_results = bd.run(stack, n_processes=1) | ||
| intensity_table = build_traces_nearest_neighbors(spot_results=spot_results, anchor_round=0, | ||
| search_radius=4) | ||
|
|
||
| assert intensity_table.shape == (2, 2, 3) | ||
| f, c, r = np.where(~intensity_table.isnull()) | ||
| assert np.all(intensity_table[Axes.ZPLANE.value] == (5, 5)) | ||
| assert np.all(intensity_table[Axes.Y.value] == (40, 20)) | ||
| assert np.all(intensity_table[Axes.X.value] == (20, 40)) |
Oops, something went wrong.